Churn rate measures a number of individuals that leave a group or other collection over a certain period of time, such as a number of subscribers that leave a subscription-based service. Churn, therefore, is similar to attrition, and may be the opposite of retention. For example, a subscriber-based service model may succeed when subscriber churn is low (and retention is high), and may fail when subscriber churn is high (and retention is low), among other things.
Industries that rely on subscription-based service models, such as the cable television industry, the cell phone industry, web-based services, and so on, spend a considerable amount of time, money, and effort attempting to identify reasons why their subscribers churn, in order to provide retention incentives to subscribers that keep them from ending use of provided services. However, their efforts often lack insight or are driven by information received directly from subscribers or from simple metrics, which may lead to ineffective results and unsuccessful determinations as to why subscribers are not being retained, among other problems.